Abstract: An information retrieval system based on probabilities that documents meet information needs. The frequency of occurrence of a representation in a collection of documents is estimated by identifying the frequency of occurrence of the representation in a sample of documents and calculating the difference between the maximum and minimum probable frequencies of occurrence of the representation in the collection. If the difference does not exceed a limit, a midpoint of the maximum and minimum probable frequencies is the estimated frequency of occurrence of the representation.Document distribution probabilities are optimized and probability thresholds are established for the identification of documents. An initial probability threshold is established and is adjusted as the probabilities are scored for documents in samples. The document result list is iteratively adjusted through the samples.

Abstract: A computer implemented process for creating a search query for an information retrieval system in which a database is provided containing a plurality of stopwords and phrases. A natural language input query defines the composition of the text of documents to be identified. Each word of the natural language input query is compared to the database in order to remove stopwords from the query. The remaining words of the input query are stemmed to their basic roots, and the sequence of stemmed words in the list is compared to phrases in the database to identify phrases in the search query. The phrases are substituted for the sequence of stemmed words from the list so that the remaining elements, namely the substituted phrases and unsubstituted stemmed words, form the search query. The completed search query elements are query nodes of a query network used to match representation nodes of a document network of an inference network.

Abstract: A computer implemented process for creating a search query for an information retrieval system in which a database is provided containing a plurality of stopwords and phrases. A natural language input query defines the composition of the test of documents to be identified. Each word of the natural language input query is compared to the database in order to remove stopwords from the query. The remaining words of the input query are stemmed to their basic roots, and the sequence of stemmed words in the list is compared to phrases in the database to identify phrases in the search query. The phrases are substituted for the sequence of stemmed words from the list so that the remaining elements, namely the substituted phrases and unsubstituted stemmed words, form the search query. The completed search query elements are query nodes of a query network used to match representation nodes of a document network of an inference network.